Applications, datasets and models built by the group. Each one is meant to be opened, not just cited.
High-resolution crowdsourced insight into extreme heat vulnerability across New York City. 250-metre grid cells score heat risk and system dynamics across 43 indicators.
A human-AI online platform leveraging knowledge graph retrieval for interdisciplinary urban intelligence and systems mapping.
Workstreams
Four threads run in parallel underneath the shipped work. Each has a named lead and is where new projects come from.
Scalable, efficient infrastructure for visualisation, analytics and simulation — the substrate every other workstream builds on.
Machine learning and data analytics for high-resolution spatial understanding: flow prediction, anomaly detection, and inference of the patterns cities leave in their data.
Agentic tools, servers and knowledge infrastructure that let frontier models reason about places rather than just describe them.
Translating research into practice through municipal partnerships, pilot digital-twin deployments, and honest assessment of what changed in the planning decisions that followed.
Depending on interest, milestones can include developing your own app or AI project, presenting it to stakeholders, releasing a code package or dataset, or publishing.
